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Network Analysis in Systems Biology

An introduction to data integration and statistical methods used in contemporary Systems Biology, Bioinformatics and Systems Pharmacology research. The course covers methods to process raw data from genome-wide mRNA expression studies (microarrays and RNA-seq) including data normalization, differential expression, clustering, enrichment analysis and network construction. The course contains practical tutorials for using tools and setting up pipelines, but it also covers the mathematics behind the methods applied within the tools. The course is mostly appropriate for beginning graduate students and advanced undergraduates majoring in fields such as biology, math, physics, chemistry, computer science, biomedical and electrical engineering. The course should be useful for researchers who encounter large datasets in their own research. The course presents software tools developed by the Ma’ayan Laboratory (http://labs.icahn.mssm.edu/maayanlab/) from the Icahn School of Medicine at Mount Sinai, but also other freely available data analysis and visualization tools. The ultimate aim of the course is to enable participants to utilize the methods presented in this course for analyzing their own data for their own projects. For those participants that do not work in the field, the course introduces the current research challenges faced in the field of computational systems biology.

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What people are saying

We analyzed reviews for this course to surface learners' thoughts about it

systems biology specialization in one review

From the Systems Biology specialization courses, this is the one from where I have learned the most, in some way the reason is because I didn't know most of Network Analysis, but now I feel familiarized with it.

also particularly appreciated in one review

I also particularly appreciated there being plenty of reference materials which are directly related to the content being provided at the end of every lecture.

explore particular areas in one review

I am a biology graduate who is now doing a Masters in Bioinformatics and I found this course extremely helpful as it covers a wide scope of topics in a (relatively) short amount of time, providing necessary background and allowing students to go off and explore particular areas of interest.

hands on learning in one review

Lacks the hands on learning experience i was looking for but a great overview.

probably quite essentially in one review

The topics were generally very well explained, but the "necessary but not required" prerequisites are probably quite essentially to getting grips with the course.

reference materials which in one review

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